The inaugural WDARF Grant Call was launched in 2017 and six projects were selected for funding support. These projects were selected on the basis of technical merit, expertise of the research team and its potential impact and contribution to Singapore's workforce development and lifelong learning.
Professor Stephen Billett (Griffith University) and Dr Anthony Leow, Republic Polytechnic
Against the backdrop of the SkillsFuture national movement to promote skills mastery and lifelong learning, the research seeks to identify and address gaps in existing educational provisions and capacities of teachers in the post-secondary education institutions (PSEIs) for employability-related continuing education and training (CET) across the Singaporean workforce. It also investigates CET educators’ viewpoints and their teaching practices by examining (i) their perspectives regarding the facilitators and barriers to CET teaching and learning, and (ii) how their professional development in the CET terrain can be realised. By investigating the CET experience from aspects of both students and CET educators in the teaching-learning partnership, the study can potentially illuminate the personal, professional and organisational dimensions of the CET experience.
Associate Professor Liaw Sok Ying, Alice Lee Centre of Nursing Studies at the National University of Singapore
The research seeks to inform professional development of clinical nurses who are critical in facilitating nursing students’ learning at work in the clinical setting. The study will explore the experiences of clinical nurses and academic educators in supporting workplace clinical teaching and learning, and examine the effects of a blended learning course to enhance workplace clinical teaching and learning. The outcomes can therefore contribute to developing a successful partnership model of best practices between healthcare workplace and academic institutions.
Professor Robert Kamei and Dr Kan Min-Yen, Institute for the Application of Learning Science and Educational Technology (ALSET) at the National University of Singapore
The aim of this study is to create a recommender system that can help Singaporeans find, select and complete CET programmes that are suited to both their personal strengths and the needs of the broader Singapore economy. It uses both recent artifical intelligence and data mining techniques as well as behavourial science to better understand how and why people pursue opportunities for lifelong learning. The pilot will test and evaluate the quality of its recommendations.